Photocollage generation and modification using image recognition

ABSTRACT

A method and system for employing image recognition techniques to produce a photocollage from a plurality of images wherein the system obtains a digital record for each of the plurality of images, assigns each of the digital records a unique identifier and stories the digital records in a database; automatically sorts the digital records using at least one date type to categorize each of the digital records according at least one predetermined criteria; employs means responsive to the sorting step to compose a photocollage from the digital records. The method and system employ data types selected from pixel data; metadata; product order information; processing goal information; or customer profile to automatically sort data typically by culling or grouping to categorize according to either an event, a person, or chronologically.

FIELD OF THE INVENTION

[0001] The invention relates generally to the field of photography, andin particular to photo collections. More specifically, the inventionrelates to employing image recognition techniques for generatingphotocollages automatically.

BACKGROUND OF THE INVENTION

[0002] Photographs, videos, and memorabilia collections are verycommonly used to maintain memories and events that formed a part of apersons life. These collections serve to augment the human memory andenrich the process of sharing stories related to the memories. Whenorganized, viewed and shared on a regular basis a collection of memoryartifacts generates a large reward, enriching the lives of all involved.The nature of these collections is such that they grow steadily, eventby event, year by year, and soon become large and difficult to manage.Collections of photos and memorabilia are considered one of the mostimportant and valued possessions by most people. They are the firstthings that people think of when forced to flee their homes due to fire,flood or other natural disaster. These collections possess intrinsic,emotional value, even if they are never viewed, because the need topreserve a memory of life is strong and universal. Because of therelative importance of these memories to the persons involved, the priorart is replete with teachings that disclose organizational methods.

[0003] The most common manner of organizing these collections within theprior art is to place the photos, videos or memorabilia into either analbum or a box. Common vinyl album pages provide the means to store andview between one and five standard sized photos per page. Creativepeople often spend hours carefully selecting and arranging photos,writing captions, clipping newspaper articles, and other memorabilia tocreate visual stories or scrapbooks. Once organized into groups or pagesthese photocollages greatly enhance a person's ability to remember andshare the story surrounding the depicted events. These simpleorganization tools allow the collections to be easily viewed and alsoserves to protect the artifacts themselves. There are numerous types ofalbums and boxes available in the market today, ranging from simplevinyl sleeves to boxes manufactured from specialized materials designedto preserve the artifacts. Album vendors include Pioneer Photo Albums,Design Vinyl and Cason-Talens. Box vendors include Exposures. None ofthese prior art disclosures provide a means by which a photocollage ofthese memorable events can be easily constructed by persons to who theseevent means so much.

[0004] As used herein photocollage refers to a single page having aplurality of images, such as a page in a photo album, or a compositeimage having a number of images relating to a single theme such as avacation, wedding, birthday party or the like. The concept ofphotocollage as used herein also includes the concept of a bound photoalbum having a plurality of pages, one or more of which is aphotocollage. Despite the fact that many people are engaged incollecting these memorable artifacts, few people have the free timeavailable to invest on a regular basis to organize and maintain them.Before long, the amount of unorganized material becomes a significantpsychological barrier to getting organized. Other barriers exist whichprevent people from actively maintaining these memorabilia collectionssuch as confidence in their process, access to the materials, orremembering the details about the event. Often, once people get startedon this organizational task they find it rewarding and fun, but still asignificant amount of work.

[0005] Many attempts have been made to provide tools for working with ororganizing photo and memorabilia collections. Computer software programssuch as Picture-It™, by Microsoft, or Creative Photo Albums™, by DogByte Development, allow people to work with digital versions of theirphotos and create digital versions of an album or print them on a homeprinter. Software products such as these require each photo or artifactexist in digital form before they can be used. Although these productsincrease the ability to change and enhance photos and scannedmemorabilia they do not reduce the amount of work needed to organizecollections or create visual stories. Other services such as Photo-Net™by PictureVision™ will scan photographs in a high-quality format at thetime of photo processing and provide a thumbnail image of the scannedimages via the Internet. A customer, using these scanned images cancreate collections of photos which can be viewed on the Internet or haveprints generated. Currently some of these services do not allow for thearrangement of several photos on a page and are limited to consumers whohave a collection of digital images and a computer connected to theInternet and who are both computer and web literate.

[0006] It should be apparent from the foregoing discussion that thereremains a need within the art for a method by which consumers can createphotocollages and photo albums (or have them made for them) in a mannerthat is as simple as ordering prints.

SUMMARY OF THE INVENTION

[0007] The present invention addresses the need for an improved methodof generating photo albums from consumer photographs that requires aminimum amount of effort but yields a high-quality product and isreasonably priced.

[0008] The present invention is directed to overcoming one or more ofthe problems set forth above. Briefly summarized, according to oneaspect of the present invention, a system and method for producing aphotocollage from a plurality of images, comprising the steps of: a)obtaining a digital record for each of the plurality of images, each ofthe digital records having a unique identifier and storing the digitalrecords in a database; b) automatically sorting the digital recordsusing at least one date type to categorize each of the digital recordsaccording at least one predetermined criteria; c) employing meansresponsive to the sorting step to compose a photocollage from thedigital records. The system then associates each of the images with atleast one of the categories followed by a sorting step that arranges theimages according to the categories. The system then employs thecategories to automatically construct the photocollage from the storedimages by generating a plurality of pages of the stored images.

[0009] These and other aspects, objects, features and advantages of thepresent invention will be more clearly understood and appreciated from areview of the following detailed description of the preferredembodiments and appended claims, and by reference to the accompanyingdrawings.

ADVANTAGEOUS EFFECT OF THE INVENTION

[0010] The present invention has the following advantages: Allows theuser to have (1) an easy method for creating professional lookingphotocollages, (2) duplication of photocollages, and (3) keepingphotocollage files for later use.

BRIEF DESCRIPTION OF THE DRAWINGS

[0011]FIG. 1 is a block diagram illustrating the basic system elementsused in practicing the present invention; and

[0012]FIG. 2 is a system diagram showing the collection steps that takeplace once a customer has delivered images to the system;

[0013]FIG. 3 is a flow diagram showing the active processing goal stepsused by the system of the present invention;

[0014]FIG. 4 is a flow chart showing the steps performed by the presentinvention; towards a story preparation based photocollage.

[0015] To facilitate understanding, identical reference numerals havebeen used, where possible, to designate identical elements that arecommon to the figures.

DETAILED DESCRIPTION OF THE INVENTION

[0016] An acceptable photo album or photocollage can be createdautomatically from customers' exposed film, negatives, or digitalimages.

[0017] Referring to FIG. 1, which is the method as envisioned by thepresent invention designed to automatically produce photocollagesincluding albums 17, CDs and other image-based keepsakes 11. The processof transforming the supplied image material into a photocollage isreferred to as Story Preparation services. Story Preparation servicesapplies the necessary amount of image understanding embodied in acollection of processing modules executed in a non-linear sequence tocreate a story representation of the images. In a preferred embodimentthese processing modules include: collecting, sorting, culling,annotating, grouping, enhancing, associating and, composing. These stepscan be performed in the order listed or they may be rearranged indifferent sequences depending upon the desired output product. Theproduction of a particular photocollage product may include one, two or,more of the available steps. Which steps are used and in what sequenceis determined by the system based upon the desired product. It isimportant to remember that the present invention envisions providingsufficient image understanding of the subject images with the ultimategoal of teaching the system to understand that there are pervasivethemes that exist within various sets of images and recognizing thesethemes thereby creating an image story product, or photocollage.

[0018] As shown in FIG. 2, the collection step begins when a customer,having completed picture taking for one or more events delivers one ormore exposed film strips or cartridges 10, digital still camera memorycards 12, photographic prints 6 or video camera media 8 to a processingfacility 14. At the time that the customer delivers the exposed filmcartridge(s) to the processing facility the customer's identity isrecorded and associated with the suite of film cartridges and otherimage sources. Alternatively the customer identity may be encoded on thefilm by exposing a machine-readable sequence of marks along the edge ofthe film or by using the magnetic coating on the Advanced Photo Systemfilm. The conventional film processing takes place with conventionalcorrection of exposed photographs to balance color and brightness andcontrast. The exposed film images are chemically processed 16 togenerate an optical image. These optical images are then scanned 18 toproduce a high-resolution digital file that is archived in a data store20. In general, to produce a high-resolution printed image of 8×10 inchsize, a resolution of 1538×1024 pixels is required. Digital Still Cameraimages from Digital Still Camera memory cards that are delivered to theprocessing facility are digitally processed 22 to produce an equivalentdigital image file of similar size and stored on the data store 20.Analog video camera images on media 8 delivered to the processingfacility are digitized and processed before storage on the data store20. At the conclusion of this step in the process there exists acollection of digital image files associated with a customer by means ofa customer identification. This collection of digital image data, orpixel data 32, is now available as a source of data for the StoryServices processing modules. Data attached or associated with individualimages or groups of images provided by the customer such as date, time,location, sound, camera identification, customer identification,exposure parameters, Advanced Photo System IX data, are all examples ofmeta-data. This meta-data 34 is stored on image store 20 and associatedwith the available pixel data 32. In addition the customer selects thedesired output product or product type from a listing of availablechoices. This selection may be indicated by the customer marking thephoto processing bag 24, verbally indicating the desired product to aclerk 26 or by input at a computer terminal or kiosk 28. The orderdescription 36 generated from any one of the indicated sources providedby the customer is stored on the system and is associated, by means of acustomer identification, with an existing customer profile 30 in thedata store 20.

[0019] At the conclusion of the collection step the pixel data,meta-data, customer profile and order description are available as inputdata for the subsequent processing steps. These steps can be performedin the order listed or they may be rearranged in different sequencesdepending upon the desired output product. The production of aparticular photocollage product may include one, two or, more of theavailable steps. Which steps are used and in what sequence is determinedby the system based upon the desired product. Following the collectionstep but before subsequent processing steps are performed, the specificprocessing to be applied to the collected set of image material isdetermined in a process goal generation step 37 and embodied in a set ofphotocollage processing goals 38. For each of the output productsrequested the system determines an optimum sequence of processing stepsto be applied. The processing of the output product or products willfollow this system determined processing sequence, unless the sequenceis modified by one of the processing modules. The processing output foreach module is stated as one or more processing step goals. Theprocessing in each step uses the stated processing step goals to controlthe logic, rules, and parameters applied during the processing of thecollected image material to satisfy the stated processing step goal orgoals. In addition to accomplishing processing goals each processingstep can also create goals for itself or future processing steps. Newgoals, which result from executing a particular processing step, reflectnecessary adjustments of desired parameters because the original goal isimpossible to achieve or the processing step may generate new goals forsubsequent processing steps. The initial set of processing goals 38 isdetermined by retrieving a default processing description from adatabase of available products 40 maintained by the system. . Once theinitial set of processing goals is determined the photocollageprocessing is initiated by the system.

[0020] As described, the automatic processing of photocollages iscarried out in processing modules employed to perform these imageunderstanding and interpretation steps. Each processing module relies ondata from a number of sources in order to satisfy the processing goal.Each processing module has access to five sources of data: pixelinformation contained in the individual images, meta-data attached toimages or groups of images, the original product or service orderdescription, the list of active processing goals maintained by thesystem and, a customer profile containing information about thecustomer. The pixel data 32 for each image provides each module with theopportunity to apply image processing and image understandingalgorithms. The meta-data 34 as used herein refers to the informationattached to the individual images and to groups of images will containinformation about the image or group of images which originated at thetime of capture or was generated in prior processing of the image orgroup of images. Date, time, location, sound, camera identification,customer identification, exposure parameters, Advanced Photo System IXdata, are all examples of meta-data that are, in a preferred embodiment,be attached to the original input images. The original product orservice order description 36 contains the specific product request fromthe customer and any notes that were captured in the ordering process.At any time in the processing of the image or group of images the systemwill have a list of active processing goals 38. Active goals are theprocessing goals for each processing module, which have yet to beaccomplished by the system. At the start of processing this list willinclude the specific product or products requested by the customer,along with the translation of these product goals into system and modulegoals. The customer profile includes both factual and uncertaininformation related to the customer. The factual data would includegeneral items such as name, address, names and ages of individuals inthe household, important dates, anniversaries, product preferences andpurchase history. In addition factual data such as face recognitionfeature vectors of the immediate family and extended family, voicetraining sets, handwriting samples, would also be included in thecustomer profile database. Uncertain information would includeprocessing goals recommended by processing modules from previous orderprocessing, image understanding assertions about the contents of theimage or groups of images which have not been verified or otherunverified information or assertions. Information and data contained inthe customer profile is updated with every order processed to reflectchanges in order preferences, order history and update uncertaininformation. In order supply the system with the necessary amount ofimage understanding required to arrange the images into set inaccordance with themes relating to predetermined criteria that must beprovided for the system to have the capability to identify attributeswithin the images. For example, in a preferred embodiment, if a customerrequests a birthday photocollage the system will retrieve the defaultprocessing goals which indicate that the steps of collecting, sorting,culling, annotating, and composing will be involved in the processing ofthe requested product. In addition the processing goals for each of themodules will reflect the default attributes necessary to process abirthday product. In this example the sorting module processing goalswill include a sort by date goal and a sort by content goal. The sort bydate processing goal is further refined to sort the images that occur onor near a target list of dates which are determined from a list of knownbirthdays retrieved from the customer profile into the photocollage.

[0021] In a preferred embodiment each processing module performsprocessing on two distinct levels: objective and subjective. Theobjective processing deals with factual information about the images orgroups of images or with data calculated deterministic algorithms.Examples of factual data include the size of the image, captureparameters, histograms, image transforms, etc. Commercially availablesoftware programs such as Adobe Photoshop® and Corel Draw® processimages using objective data. Subjective processing deals withinformation that is uncertain or data is the result of non-deterministicalgorithms. Often subjective results carry with them a confidence factorwhich allows subsequent processing steps to interpret the results.Usually subjective results occur when attempting to determine abstractinformation about an image or group of images. Examples of this type ofthe processing would be face detection, face recognition, facialexpression determination, location determination, assertions,interpretations, etc. Commercially available software programs such asFaceIT© by Visionics Corp. process images to associate faces in imageswith names and other information. Some processing modules process onlysubjective information, others process only objective information andstill others process both.

[0022] As shown in FIG. 3 the processing of a photocollage is directedby the system using the active processing goals 38, 48, and 49. Becausethe processing goals are non-deterministic, vary by requested productand may be modified during the processing there exist a large number ofpossible processing sequences. The progression of processing applied tothe collected image material is applied in sequential steps. Each stepimplements a single processing module that is intended to satisfy orpartially satisfy an active processing goal. At each step in the processany one of the available processing modules (culling 62, grouping 64,enhancing 66, annotating 68, associating 70, or composing 72) may beexecuted. At the conclusion of the processing of a particular step theactive processing goals 38 that existed before the step processing areupdated to reflect the changes in goals that resulted from the executionof the processing step 52. These updated active processing goals 48serve as the input processing goals for the subsequent processing step53. Each of the available processing modules will be described. Inaddition to the processing goals 38, 48, and 49, the processing modulesat each processing step have access to four sources of information:pixel data 32 contained in the individual images, metadata 34 attachedto images or groups of images, the original product or service orderdescription 36 and, a customer profile 30 containing information aboutthe customer. This process can iterate as many times as necessary tocomplete the desired product objectives.

[0023] The processing of the collection of digital image material isreviewed to remove unwanted images. This step is called culling. Cullingis performed on images that are deemed unwanted due to poor quality, orif there are several images that are similar in composition and only oneis desired. To accomplish this culling process involves the computationof several image based metrics using the pixel data 32. These metricsfall into two basic categories: technical quality measures and abstractfeature metrics. The technical quality measures would involvecalculations to assess the overall sharpness of the image, exposurequality, grain quality of the image. Algorithms used to calculatetechnical quality measures are common in the art, examples wouldinclude: “Estimation of Noise in Images: An Evaluation” by S. I. Olsonin, 55 (4), 1993, pp. 319-323 and “Refined filtering of image noiseusing local statistics” by J. S. Lee in Computer Vision Graphics andImage Processing, 15, 1981, pp. 380-389.

[0024] Images are then given an overall rating of technical qualitybased on the technical quality metrics. The overall image quality metricis then compared to a threshold associated with the processing goal.Images whose quality rating falls below the threshold are flagged asunwanted. The specific threshold applied to a given image or set ofimages is parametrically determined using the processing goal 38 and thecustomer profile 30 as inputs. In addition to the determination ofspecific objective image features, abstract subjective image featuresare also calculated. These subjective measures of the image allow themodule to cull unwanted or unnecessary images. A typical example ofimages which require culling occurs when several images in the group aresimilarly composed and contain nearly identical content such as a groupphoto which is repeated several times. In order to choose the best ofthis group of images the digital image is analyzed to determine aquality metric composed of both objective and subjective qualityfeatures. The basis for this subjective assessment would be the presenceor absence of faces, the identification of the faces in the image, thenumber of faces present, if the eyes are open on each face, if thesubject is smiling, or orientation of the face to the camera. Examplesof algorithms used to determine subjective features of an image aredescribed in Proceedings of the IEEE Computer Society conference onComputer Vision and Pattern Recognition, June 1997. These subjectivefeatures provide clues about the subjective quality of the image. Theobjective and subjective features calculated for each image are combinedand the images are ranked according to the relative importance of eachfeature analyzed to the processing goal 38 and which matches the storedcustomer preferences 30. The ranking, because it is partially based uponsubjective information also carries a probability weighting factor. Thecombination of the ranking and the probability weighting factor is usedto assert a decision about the quality of the image. This qualityassertion is retained with the image as metadata 34 and is passed to thenext processing step. In the grouping step images are grouped accordingto criteria derived from the analysis of the customer profile 30, theactive processing goals 38 and the requested product or service 36. Thegoal of grouping images is to associate images that are a part of acommon theme or story in the mind of the customer. Typical groupingsderived from customer profiles 30 would be to associate images accordingto the preferred organization scheme of the customer. The attributes oftypical organization schemes would include organizing by events such asbirthday party, vacation, holiday, graduation, organizing by time, andorganizing by people. Customer requested products 36 could also dictategrouping parameters in accordance with the product design. Examples ofthese grouping schemes include grouping by location in a theme park, bycommon life-cycle event such as graduation, by image content type suchas outdoor, indoor, nature, person, group, etc. A variety of softwarealgorithms exist which are applicable to grouping. One class of softwarealgorithms operates on metadata 34 associated with the image where thegrouping process is similar to searching a media database. Severalcommercial examples of media databases that allow searching are PictureNetwork Incorporated, Publishers Depot (www.publishersdepot.com). Asecond class of algorithms employed for this grouping process wouldinclude image processing algorithms which identify objects and featuresets within an image by way of the pixel information 32. These objectscould represent typical cultural icons such as birthday cakes, Christmastrees, graduation caps, wedding dresses, etc. An example of suchalgorithms is reported by J. Edwards and H. Murase, “Appearance Matchingof Occluded Objects Using Course-to-fine Adaptive Masks” in Proceedingsof the IEEE Computer Society Conference on Computer Vision and PatternRecognition, June 1997, pp. 533-546. The Product Order Information 36can also be used in this grouping by simply stating the event orlocation or person on which to base the final product. The ProcessingGoals 38 can also be used as a grouping tool where the specific productsoffered mandate a specific grouping.

[0025] The annotation step seeks to generate annotation that can becomposed on the story product or photocollage. Annotation is designed toprovide context information about the image or group of images andassist the customer in communicating the story surrounding the images. Avery common form of annotation is text associated with each image andwith a group of images which explains the “who, what, when, where, andwhy”. Such context information is generally derived from metadata 34generated in previous processing steps, user profiles 30 or, imageunderstanding algorithms applied in the annotation module. “Who”information may be determined using face recognition algorithms appliedto the pixel data 32 tuned by the training data contained in thecustomer profile 30. Using a commercial product such as “Facelt” byVisionics, a database of known faces can be retrieved from the customerprofile 30 and used to guide the face recognition software. “What”information can be asserted by correlating date and time of the imagecapture available in the image metadata 34 with key dates contained inthe customer profile 30. In addition more “what” data can also beasserted by looking within the image 32 for specific cultural icons,derived from object recognition algorithms, such as birthday cakes,Christmas trees or, graduation robes. “When” information for annotationis easily determined using metadata 34 such as date and time recorded atthe time of capture. “Where” information may be provided from thecapture device integrated with GPS (Global Positioning System)technology and then added to the metadata 34 for the image or it can beguessed at using image understanding algorithms which correlate knownlocation scenes with the image content from available images 32. “Why”information is very difficult to determine without some input from theimage owner via the product order information 36. The annotation, oncedetermined, can be rendered as text, graphics, images, video or soundand associated with the individual images or with the group of images ineither a traditional photocollage or digital product.

[0026] The image enhancement module applies image processing to improvethe image for the intended story based purpose. Two categories of imageenhancement are considered for each image. Basic image enhancements areapplied to all images, as necessary, would include: red-eye removal,brightness and contrast adjustment, color adjustment, and crop and zoomto improve composition. Image enhancements are applied directly to thepixel data 32 and recorded in the image metadata 34 from the images. Asecond category of image enhancement is applied to the images in orderto enhance their use within a story context to communicate the emotionor to support the story theme as described in the processing goal 38.For instance, selected images from a wedding story would be softenedusing a blur algorithm or the colors of an image could be made to matchthose found in a comic strip. The application of this type ofenhancement processing is either specified in the product description 36generated from the customer profile 30. All of these operations areavailable in image editing software programs such as Adobe PhotoShop,with the exception of red-eye removal and red-eye removal can beaccomplished via the Kodak Imaging Workstation and other software suchas Picture-It from Microsoft.

[0027] Some product specifications will include a processing goal toassociate external content that is relevant to the product and the imagecontent. This associated content provides additional context andinterest in the final rendered product. External content takes severalforms including weather reports, newspaper headlines, stock photographs,advertisements, historical references, travel brochure copy, popularmusic clips, video segments, etc. In order to locate and findappropriate content for the image story/photocollage the metadata 34attached to each image and image group and is interrogated to derivesearchable topics or specific information located in the customerprofile 30. These search topics would focus on the when, where, whataspects of the image story. Once a series of potential search topicshave been assembled they are formatted into queries and searches areperformed on a variety of databases. The results of these contentqueries is then refined by applying priority rules from the productdescription database and customer preferences stored in the customerprofile 30. These types of searches are common in information databasessuch as Yahoo® on the internet (www.yahoo.com) or from Dialog corp. Ifthere are items within the image that can be identified with specificevents (such as a wedding or birthday) or if a person can be identifiedfrom imaging algorithms, the Pixel Information 32 is used to determiningthe types of additional content that are added. The Processing Goals 38dictate the forms and types of associated content that is added. TheProduct Order Information 36 is also a source of information regardingthe association of content by a special request on the form (such as atheme park or wedding motif).

[0028] The layout processing module places the image data, annotations,and associated content into an output ready format. This layout stepmust be repeated for each product that was requested by the customer andfor each layout goal that was generated during the processing steps. Themain task involved in the layout of a multi-page photocollage is thedetermination of which images are to be placed in specific locations onspecific pages. In addition the external content which has beenassociated with the individual images or groups of images must becomposited onto the page. The layout process may be accomplished innumerous ways. One means of performing this processing step is to employa parametric photocollage description. This description specifies thegeneral structure of the photocollage but is not sufficient, of itself,to specify a final photocollage product. The description file includesphotocollage features such as number of sections, size and format ofindividual pages, maximum and minimum number of pages allowable, maximumand minimum number of customer images allowable per page, sectiondescriptions, cover designs, location of allowable stock content, etc.By employing a photocollage description file a variety of tailoredphotocollage products may be designed incorporating features specific tothe design goals. The layout step begins by reading the photocollagedescription file to initialize a layout algorithm. The layout algorithmthen works page by page and section by section to apply specific layoutrules guided by the values in the photocollage description file. Avariety of page/section layout algorithms could be employed which embodydifferent design philosophies for photocollage products. The finalphotocollage product can be rendered on a variety of output media typeswhich would include paper, fabric, as a digital file or on any one of anumber of digital media forms such as a CD. The Processing Goals 38 areused to determine the capabilities of the specific devices being used.Customer Profiles 30 are used to determine color preferences, layoutpreferences, and design considerations. Metadata 34 is used to determinethe placement of associated content with specific images.

[0029]FIG. 4 shows the system diagram for Story Preparation Services.Input to the system comes from Personal Computers 90 (using albumingsoftware such as Microsoft Picture It, Family Base from Micro Dynamicsor a myriad of others), an interactive kiosk, via the phone orover-the-counter order forms 84, a retail outlet 82 with links to thesystem, or digitization services 80 specializing in converting analogmaterial into digital information. The information needed to perform thestory services is communicated via traditional means including mail,phone, modem, Internet or other on-line services. The componentsrequired by such as system include a digitization system for pictures,video and audio 104, a storage facility 102, an operator interface 96,algorithms and software 98 for the analysis of the data and to providethe necessary steps to complete the product, and an output deliverysystem 100 for printing or other media.

[0030] The invention has been described with reference to a preferredembodiment. However, it will be appreciated that variations andmodifications can be effected by a person of ordinary skill in the artwithout departing from the scope of the invention.

PARTS LIST

[0031]6 photographic prints

[0032]8 camera media

[0033]10 cartridges

[0034]11 keepsakes

[0035]12 memory cards

[0036]14 processing facility

[0037]15 CDs

[0038]17 albums

[0039]20 data store

[0040]22 digital processing

[0041]24 processing bag

[0042]28 kiosk

[0043]32 pixel data

[0044]34 meta-data

[0045]36 order description

[0046]37 goal generation

[0047]38 processing goals

[0048]40 products

[0049]48 processing goals

[0050]49 processing goals

[0051]62 culling

[0052]64 grouping

[0053]66 enhancing

[0054]68 annotating

[0055]70 associating

[0056]72 composing

What is claimed is:
 1. A method of producing a photocollage from aplurality of images, comprising the steps of: a) obtaining a digitalrecord for each of the plurality of images, each of the digital recordshaving a unique identifier and storing the digital records in adatabase; b) automatically sorting the digital records using at leastone date type to categorize each of the digital records according atleast one predetermined criteria; c) employing means responsive to thesorting step to compose a photocollage from the digital records.
 2. Themethod according to claim 1 wherein the step of automatically sortingfurther comprises as the at least one data type, a data input that isselected from one of the following: (pixel data; metadata; product orderinformation; processing goal information; or customer profile).
 3. Themethod according to claim 1 wherein the sorting step further comprisesemploying one of the following: (culling or grouping).
 4. The method ofclaim 1 wherein the sorting step further comprises categorizingaccording to one of the following: (an event; a person; orchronologically).
 5. The method of claim 1 wherein the predeterminedcriteria further comprises analyzing pixel data for quality andduplicate images.
 6. The method of claim 1 wherein the categorization isdetermined by grouping according to image related information.
 7. Themethod of claim 6 wherein the image related information used in thesorting step is selected from either: (an event; location; chronology;personal information; objective criteria; or subjective criteria). 8.The method of claim 1 wherein the step of obtaining further comprisesobtaining with the digital record data relating to one of the following:(metadata; customer profile information; or product order information).9. The method of claim 1 wherein the step of employing means responsivefurther comprises employing one of the following: (metadata; pixelinformation; processing goals; customer information or product orderinformation).
 10. The method of claim 9 wherein the step of employingmeans responsive further comprises applying one of following(enhancements; associations; annotations; or layouts) to compose thephotocollage.
 11. The method according to claim 1 wherein the step ofobtaining further comprises scanning the images to obtain the digitalrecords of the images.
 12. The method according to claim 1 wherein thestep of obtaining the digital records further comprises receiving thedigital records of the images via communication means.
 13. The methodaccording to claim 1 wherein the step of obtaining the digital recordsfurther comprises providing the digital records of the images.
 14. Themethod according to claim 1 wherein the step of obtaining furthercomprises obtaining the plurality of images with identificationinformation.
 15. The method according to claim 1 wherein the step ofobtaining further comprises the gathering of additional data with regardto the plurality of images.
 16. The method of claim 15 wherein theadditional data is metadata selected from one of the followingcategories: (date; time; location; Advanced Photo Standard informationon exposure, sound files, or camera identification number).
 17. Themethod according to claim 15 wherein the step of gathering additionaldata further comprises the collecting of customer order information. 18.The method according to claim 15 wherein the gathering of additionaldata includes maintaining a customer profile pertinent to creatingphotocollages.
 19. The method according to claim 18 wherein the step ofsorting the digital records further comprises using the customer profileas at least a portion of the predetermined criteria.
 20. A method ofproducing a photocollage from a plurality of images, comprising thesteps of: a) obtaining a digital record for each of the plurality ofimages, each of the digital records having a unique identifier andstoring the digital records in a database; b) analyzing the digitalrecords to obtain information with respect to at least one attribute ofthe digital records; c) employing computational means for sorting saiddigital records in accordance with the at least one attribute; and d)applying the at least one attribute according to a predeterminedcriteria using the computational means to compose a photocollage. 21.The method according to claim 20 wherein the step of analyzing thedigital records further comprises analyzing the digital records inaccordance with customer profiles to determine the at least oneattribute of the digital records.
 22. The method according to claim 20wherein the step of analyzing further comprises analyzing at least oneobjective feature of the digital records of the images to determine theat least one attribute.
 23. The method according to claim 20 wherein thestep of analyzing further comprises analyzing at least one subjectivefeature of the digital records to determine the at least one attribute.24. The method according to claim 20 wherein the step of automaticallysorting the digital records further comprises identifying and collectingtogether duplicates of the digital records.
 25. The method according toclaim 20 wherein the step of employing computational means for sortingthe digital records further comprises identifying and collectingtogether digital records of the images that have a subjective qualityrating below a predetermined threshold.
 26. The method according toclaim 20 wherein the step of employing computational means for sortingthe digital records further comprises identifying and collectingtogether digital records of the images that have a objective qualityrating below a predetermined threshold.
 27. The method according toclaim 20 wherein the step of employing computational means for sortingsaid digital records in accordance with the at least one attributefurther comprises applying one of the following attributes: (event;location; chronology; personal information; objective criteria; orsubjective criteria).
 28. The method according to claim 20 wherein thestep of analyzing the digital records further comprises automaticdetermination of annotations for the digital records.
 29. The methodaccording to claim 20 wherein the step of applying further comprisesenhancing the digital records.
 30. The method according to claim 20wherein the step of applying further comprises placing and associatingannotations with the digital records in the photocollage.
 31. The methodaccording to claim 20 wherein the step of applying further comprisesdetermining additional content to be included in the photocollage. 32.The method according to claim 20 wherein the step of applying furthercomprises placing additional content within the photocollage.
 33. Themethod according to claim 20 wherein the step of applying furthercomprises placing the digital records into the photocollage according tothe predetermined criteria.
 34. A system for producing a photocollagefrom a plurality of images, the system comprising: a) a device forobtaining a digital record for each of a plurality of images; b) meansfor automatically sorting the digital records in accordance with atleast one predetermined criteria; and c) means for composing aphotocollage of the digital records in accordance with the predeterminedcriteria.
 35. The system of claim 34 wherein the device for obtaining adigital record further comprises computational means for uniquelyidentifying the digital records.
 36. The system of claim 34 wherein thepredetermined criteria further comprises a data type that is selectedfrom one of the following: (pixel data; metadata; product orderinformation; processing goal information; or customer profile).
 37. Thesystem according to claim 34 wherein the means for sorting furthercomprises applying the at least one predetermined criteria to sort interms of one of the following: (culling or grouping).
 38. The system ofclaim 34 wherein the means for sorting further comprises categorizing toone of the following: (an event; location; chronology; personalinformation; objective criteria; or subjective criteria).
 39. The systemof claim 34 wherein the means for sorting categorizes by culling thedigital records employing an analysis of pixel data for quality andduplicate images.
 40. The system claim 34 wherein the means for sortingcomprises categorizing mean for grouping according to image relatedinformation.
 41. The system of claim 40 wherein the image relatedinformation used in the means for sorting is image related informationrelating to either: (an event; location; chronology; personalinformation; objective criteria; or subjective criteria).
 42. The systemof claim 34 wherein the means for composing further comprises meansresponsive to the means for sorting for employing one of the following:(metadata; pixel information; processing goals; customer information orproduct order information).
 43. The system of claim 42 wherein the meansresponsive further comprises applying one of following (enhancements;associations; annotations; or layouts) to compose the photocollage. 44.The system according to claim 34 wherein the device for obtaining adigital record further comprises means for scanning the images to obtainthe digital records of the images.
 45. The system according to claim 34wherein the device for obtaining a digital record further comprisesmeans receiving the digital records of the images via communicationmeans.
 46. The system according to claim 34 wherein the device forobtaining a digital record further comprises providing the digitalrecords of the images.
 47. The system according to claim 34 wherein thedevice for obtaining a digital record of the plurality of images furthercomprises means for creating a digital identification for each of thedigital records from identification information provided within eachrespective of the plurality of images.
 48. A system for producing aphotocollage from a plurality of images, comprising: a) computationalmeans operatively connected to a device for obtaining a digital recordfor each of the plurality of images, each of the digital records havinga unique identifier and storing the digital records in a database; b)means for analyzing the digital records within the computational meansto obtain information with respect to at least one attribute of thedigital records; c) means for sorting the digital records in accordancewith the at least one attribute within the computational means; and d)means for applying the at least one attribute according to apredetermined criteria using the computational means to compose aphotocollage.
 49. The system of claim 48 wherein the means for analyzingsaid plurality of images further comprises analyzing the plurality ofimages in accordance with customer profiles to determine at least onesaid attribute of said plurality of images.
 50. The system of claim 48wherein the means for analyzing further comprises analyzing at least oneobjective feature of the digital records of the images to determine theat least one attribute.
 51. The system of claim 48 wherein the means ofanalyzing further comprises analyzing at least one subjective feature ofthe digital records to determine the at least one attribute.
 52. Themethod according to claim 48 wherein the means for sorting the digitalrecords further comprises means for identifying and collecting togetherduplicates of the digital records.
 53. The system of claim 48 whereinthe means for sorting the digital records further comprises means foridentifying and collecting together digital records of the images thathave unacceptable quality.
 54. The system of claim 48 wherein the meansfor sorting the digital records further comprises means for sorting inaccordance with the at least one of the following attributes: (event;location; chronology; personal information; objective criteria; orsubjective criteria).
 55. The system of claim 48 wherein the means foranalyzing the digital records further comprises means for determinationof annotations associated with the digital records.
 56. The system ofclaim 48 further comprising within the means for applying means forenhancing of the digital records used in creating the photocollage. 57.The system of claim 48 wherein the means for applying further comprisesmeans for placing and associating annotations with the digital recordsin the photocollage.
 58. The system of claim 48 wherein the means forapplying further comprises means for placing the digital records in thephotocollage according to the predetermined criteria.
 59. The system ofclaim 48 further comprising means for generating a visually discernableversion of the photocollage.
 60. The system of claim 48 furthercomprising means for creating a digital recording of the photocollage.61. The system of claim 48 further comprising an operator interface tocommunicate with the computational means.